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| http://dx.doi.org/10.1056/NEJMc2005696 | DOI Listing |
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Mathematical models of viral dynamics are crucial in understanding infection trajectories. However, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load data often includes limited sparse observations with significant heterogeneity. This study aims to: (1) understand the impact of patient characteristics in shaping the temporal viral load trajectory and (2) establish a data collection protocol (DCP) to reliably reconstruct individual viral load trajectories.
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